Function Of Alloy Composition Research Articles

Effects of lattice and mass mismatch on primary radiation damage in W-Ta and W-Mo binary alloys

The fundamental mechanisms of radiation damage in metal alloys of equiatomic composition are of great research interest due to the possibility to use them as new materials for radiation-hard environments. With W-Ta and W-Mo alloys as examples, this study investigates the effect of two factors, namely the difference in lattice parameters and the difference in masses of the constituent elements, on primary radiation damage by means of atomistic simulations. We compare the trends obtained with the available embedded atom method (EAM) interatomic potential and the tabulated Gaussian approximation potential (tabGAP). We observe a similar trend in the number of surviving defects as a function of alloy composition in W-Mo for both potentials, while the absolute numbers are fairly different. The tabGAP predicts higher resistance to irradiation, i.e. fewer surviving defects after the cascades. On the contrary, the trends of the dependence of surviving defects on alloy composition in W-Ta alloys are very different in the two potentials. We explain this difference by analyzing the threshold displacement energies (TDE) and melting temperatures in these alloys. The mass difference in W-Mo alloys results in Mo atoms with higher TDE in W-Mo alloys. The effect of the lattice parameter mismatch in W-Ta alloys is visible in the change of the number of surviving defects with increase of the W content in W-Ta alloys.

Tension–Compression Flow Asymmetry as a Function of Alloy Composition in the Al-Si System

Tension–Compression Flow Asymmetry as a Function of Alloy Composition in the Al-Si System

Structural and thermodynamic properties of quasi-2D Mo(1–x)W x (S, Se, Te)2 monolayer alloys: a statistical first principle study

In this work, we report an ab initio study of the structural and thermodynamic properties of two-dimensional transition-metal dichalcogenides (2D-TMDC) alloys, Mo(1–x)W x (S, Se, Te)2, using the cluster expansion framework to compute the Helmholtz free energy of alloys as a function of alloy composition and temperature, in the framework of the generalized quasi-chemical approximation. We consider alloying only on the metal sublayer. Our results indicate a weak dependence of the structural properties (lattice constants, nearest-neighbor bond lengths, and layer width) on the alloy composition (i.e. concentrations of W and Mo atoms), in line with the very similar values of the atomic radii of Mo and W atoms. A stronger dependence on the chalcogen is obtained, a trend that reflects the larger variations in atomic radii among the three chalcogen species. As a function of composition, the structural parameters we examined show similar trends, with negligible bowing (i.e. deviations from a Vegard’s law interpolation between end compounds), for the three alloys. Moreover, already at 300 K the behavior of these structural features as a function of composition is very similar to that of the standard-regular-solution (SRS) high-temperature limit. In contrast, the electronic band gaps of the the three alloys as a function of composition show small but significant bowing, as high as −1% to −2% near the x = 0.5 alloy composition. Similarly to the structural features, the band gaps attain the high-temperature SRS limit already at 300 K. Regarding thermodynamic properties, we obtain negative values of the internal energy of mixing for the three alloys over the full range of compositions. Therefore, the theoretical alloying phase diagram for the three alloys is featureless, with stability of a fully-mixed alloy at all temperatures and compositions, with no miscibility gap (hence no bimodal nor spinodal decomposition lines). The thermodynamic potentials (mixing internal energy, mixing entropy, and mixing free energy) reach the high-temperature limit at ∼1000 K, the temperature range of synthesis of 2D-TMDC alloys. These trends of structural and electronic properties of the 2D-TMDC alloys are due to the very similar atomic radii and the nearly identical coordination chemistry of Mo and W. Our results are in agreement with experimental work on the alloying of Mo and W atoms, for samples of Mo(1–x)W x S2 monolayer alloys, that found that the random mixed alloy is the thermodynamically stable state for this alloy, with no segregation or phase separation.

Dielectric function of CuBrxI1−x alloy thin films

We study the dielectric function of ${\mathrm{CuBr}}_{x}{\mathrm{I}}_{1\ensuremath{-}x}$ thin film alloys using spectroscopic ellipsometry in the spectral range between 0.7 eV and 6.4 eV, in combination with first-principles calculations based on density functional theory. Through the comparison of theory and experiment, we attribute features in the dielectric function to electronic transitions at specific $\mathbf{k}$-points in the Brillouin zone. The observed band gap bowing as a function of alloy composition is discussed in terms of different physical and chemical contributions. The band splitting at the top of the valence band due to spin-orbit coupling is found to decrease with increasing Br-concentration, from a value of 660 meV for CuI to 150 meV for CuBr. This result can be understood considering the contribution of copper $d$ orbitals to the valence band maximum as a function of the alloy composition.

Novel InGaSb/AlP Quantum Dots for Non-Volatile Memories.

Non-volatile memories based on the flash architecture with self-assembled III-V quantum dots (SAQDs) used as a floating gate are one of the prospective directions for universal memories. The central goal of this field is the search for a novel SAQD with hole localization energy (Eloc) sufficient for a long charge storage (10 years). In the present work, the hole states' energy spectrum in novel InGaSb/AlP SAQDs was analyzed theoretically with a focus on its possible application in non-volatile memories. Material intermixing and formation of strained SAQDs from a GaxAl1-xSbyP1-y, InxAl1-xSbyP1-y or an InxGa1-xSbyP1-y alloy were taken into account. Critical sizes of SAQDs, with respect to the introduction of misfit dislocation as a function of alloy composition, were estimated using the force-balancing model. A variation in SAQDs' composition together with dot sizes allowed us to find that the optimal configuration for the non-volatile memory application is GaSbP/AlP SAQDs with the 0.55-0.65 Sb fraction and a height of 4-4.5 nm, providing the Eloc value of 1.35-1.50 eV. Additionally, the hole energy spectra in unstrained InSb/AlP and GaSb/AlP SAQDs were calculated. Eloc values up to 1.65-1.70 eV were predicted, and that makes unstrained InGaSb/AlP SAQDs a prospective object for the non-volatile memory application.

Critical Pitting Temperature of Stainless Steel: Deterministic Vs. Probabilistic Behavior

The concept of the critical pitting temperature (CPT), which is described as the temperature below which stable pits are not formed regardless of applied potential and exposure time, has received considerable attention in the literature. Over the past few decades, many attempts have been made to assess the CPT of stainless steel as a function of alloy composition, alloy microstructure, bulk solution composition, and surface roughness. In contrast to the pitting potential, which is known to be probabilistic in nature, CPT is believed by most to be a deterministic phenomenon that can be measured within a few degrees Celsius [1]. This notion has been validated by many authors who have observed a narrow range of CPT for several alloy/environment combinations [2,3]. Some authors have recently challenged this idea by reporting scattered CPT values [4]. This work seeks to determine whether the CPT falls within a narrow or wide temperature range (i.e., is CPT a deterministic or probabilistic phenomenon?).To answer this question, potentiostatic CPT measurements were performed using 1 cm² 904L stainless steel electrodes and an applied potential of 750 mV (Ag/AgCl). Temperature was increased at a rate of 1 °C/min, and the CPT was determined using the temperature at which current density rapidly increased. The CPT of 904L stainless steel was measured in four different conditions to evaluate the effect of bulk Cl⁻ concentration (0.05 and 1.0 M NaCl), passivation in 20 vol.% HNO3, and the presence of a corrosion inhibitor (0.02 M NaNO3).Figure 1 shows a cumulative graph of the CPT values of 904L obtained using the four different conditions. In this graph, n is the number of the n th pitted sample and N is the total number of experiments (i.e., 10). For all test conditions, the CPT was measured within ± 1.8 °C, which is in agreement with the reproducible CPT values reported by others [3]. Figure 1 shows that the CPT of 904L is independent of passivation in HNO₃. Further, decreasing bulk solution aggressiveness from 1.0 M NaCl to 0.05 M NaCl does not result in scattered CPT values. However, some authors have reported a considerably broader range (i.e., ± 10 °C) for the CPT of stainless steel (AISI 316L and 2205), as discussed previously. One possible explanation for their larger reported CPT range is the occurrence of crevice corrosion at the interface of the alloy/inert support (e.g., epoxy mount), which results in an inaccurate CPT measurement. To evaluate this hypothesis, the current density vs. temperature curves for two conditions were compared (see Figure 2). The blue and red curves show potentiostatic polarization results for pure pitting corrosion (i.e., crevice-free CPT measurement) and pitting + crevice corrosion, respectively. The gradual increase of the current density with temperature for the red curve suggests the presence of a crevice at the alloy/epoxy interface, which was confirmed using SEM to characterize the electrode post-polarization. On the other hand, when no crevice corrosion occurs, the current density shows a sudden increase at the CPT.The results of this study reveal that the CPT of 904L can be measured to within ± 1.8 °C, regardless of bulk solution aggressiveness (e.g., 1.0 M NaCl and 0.05 M NaCl solution) or passive state before polarization. This finding is in contrast to what some authors have suggested recently. The scattered CPT values reported in the literature are most likely due to contributions from both pitting + crevice corrosion rather than pitting corrosion alone. Acknowledgments Financial support provided by Natural Sciences and Engineering Research Council of Canada (NSERC) is gratefully acknowledged.

Accuracy of the Shardt–Elliott–Connors–Wright equation for predicting the surface tension of metal alloys

Surface tension influences the processing of molten metals including welding, soldering, refining, and casting, but it is challenging to measure at high temperatures, and thus it is an important property to predict. In particular, the surface tension of metal alloys is crucial to predict as a function of alloy composition and temperature. Previously, we developed the Shardt–Elliott–Connors–Wright (SECW) model that has the advantage of being able to predict the surface tension of mixtures as a function of composition and temperature using as inputs only the temperature dependence of pure components and the composition dependence at a single reference temperature. This model has been shown to be accurate for a broad range of non-metal mixtures. In this work, we extend the applicability of our model to six metal alloy systems, resulting in an absolute average percent deviation from experimental measurements of 1.9% over all studied compositions and temperatures ranging between 513 K and 1503 K (419 experimental data points).

Machine learning-based model of surface tension of liquid metals: a step in designing multicomponent alloys for additive manufacturing

The surface tension (ST) of metallic alloys is a key property in many processing techniques. Notably, the ST value of liquid metals is crucial in additive manufacturing processes as it has a direct effect on the stability of the melt pool. Although several theoretical models have been proposed to describe the ST, mainly in binary systems, both experimental studies and existing theoretical models focus on simple systems. This study presents a machine learning model based on Gaussian process regression to predict the surface tension of multi-component metallic systems. The model is built and tested on available experimental data from the literature. It is shown that the model accurately predicts the ST value of binaries and ternaries with high precision, and that identifying certain trends in the ST values as a function of alloy composition is possible. The ability of the model to extrapolate to higher-order systems, especially novel concentrated alloys (high entropy alloys, HEA), is discussed.

Using Feature-Assisted Machine Learning Algorithms to Boost Polarity in Lead-Free Multicomponent Niobate Alloys for High-Performance Ferroelectrics.

To expand the unchartered materials space of lead‐free ferroelectrics for smart digital technologies, tuning their compositional complexity via multicomponent alloying allows access to enhanced polar properties. The role of isovalent A‐site in binary potassium niobate alloys, (K,A)NbO3 using first‐principles calculations is investigated. Specifically, various alloy compositions of (K,A)NbO3 are considered and their mixing thermodynamics and associated polar properties are examined. To establish structure‐property design rules for high‐performance ferroelectrics, the sure independence screening sparsifying operator (SISSO) method is employed to extract key features to explain the A‐site driven polarization in (K,A)NbO3. Using a new metric of agreement via feature‐assisted regression and classification, the SISSO model is further extended to predict A‐site driven polarization in multicomponent systems as a function of alloy composition, reducing the prediction errors to less than 1%. With the machine learning model outlined in this work, a polarity‐composition map is established to aid the development of new multicomponent lead‐free polar oxides which can offer up to 25% boosting in A‐site driven polarization and achieving more than 150% of the total polarization in pristine KNbO3. This study offers a design‐based rational route to develop lead‐free multicomponent ferroelectric oxides for niche information technologies.

Performance of in situ oxidized platinum/iridium alloy Schottky contacts on (001), (2¯01), and (010) β -Ga2O3

The performance of β-Ga2O3 Schottky contacts (SCs) fabricated using amorphous, intentionally oxidized platinum–iridium alloys was investigated as a function of alloy composition and β-Ga2O3 crystal orientation. PtyIr(1−y)Ox SCs with Pt fractions of y = 0.8, 0.5, and 0.3 were deposited on (001), (2¯01), and (010) single-crystal β-Ga2O3 substrates via the reactive rf and dc co-sputtering of Pt and Ir targets using oxygen–argon plasmas. In each case, the PtyIr(1−y)Ox SCs were highly rectifying with current rectification ratios (at ±3 V) of 11/10/9 orders of magnitude (at 300 K) for the (001)/(2¯01)/(010) β-Ga2O3 substrates. Current–voltage (I–V) and capacitance–voltage (C–V) measurements revealed that the Pt0.5Ir0.5Ox SCs contained the highest Schottky barriers on all β-Ga2O3 crystal faces, with the best contacts having ideality factors of 1.05 and image-force-corrected I–V and C–V determined barrier heights of 2.10 and 2.20 eV, respectively. These were consistently higher by ∼0.2 eV than the corresponding barriers for the Pt0.8Ir0.2Ox and Pt0.3Ir0.7Ox SCs, with the Pt0.5Ir0.5Ox SCs also having significantly lower reverse leakage currents (in the 0 to −100 V range). In comparison, the barrier heights of the best unoxidized plain-metal Pt0.5Ir0.5 SCs were only ∼1.2 eV, illustrating the effectiveness of in situ oxidation in improving the performance of PtIr SCs. All PtyIr(1−y)Ox SCs on (2¯01) β-Ga2O3 showed excellent high-temperature performance with rectification ratios (at ±3 V) of 109 at 300 °C and of 106 at 500 °C.

Thermodynamic prediction of thermal diffusivity and thermal conductivity in Mg–Zn–La/Ce system

• Heat dissipating Mg–Zn–La/Ce alloys were designed based on thermodynamic database. • τ 1 phases have more negative influence on thermal diffusivity than REMg 12 . • Solute atom is dominant factor affecting thermal conductivity of Mg–Zn–RE alloys. • The thermal diffusivities of Mg–Zn–La/Ce alloys were predicted by CALPHAD method. Basic thermal properties and mechanical properties are critical parameters for the structural magnesium alloys. Solute atoms and second phases can improve mechanical properties, but are deteriorating the heat dissipation performance. Through experimental determination of alloys, it is found that REMg 12 phases have fewer negative impacts on thermal diffusivities than τ 1 phases. With the same intermetallic compound, the solute atom Zn have more negative influences on thermal diffusivities of Mg–Zn–La/Ce alloys than the content of second phases. In order to quantitatively evaluate thermal conductivities and further design Mg alloys with both high strength and high thermal conductivity, a calculated method is provided to describe the thermal diffusivity of alloys as a function of alloy composition and phase constitution. A set of parameters for expression of thermal diffusivity of Mg–Zn–La/Ce alloys were obtained through assessing the experimental data. The thermal conductivities of Mg–Zn–La/Ce system were predicted and agreed well with experimental values with calculation error of 1.6% and standard error of ±3.0 W/(m K). The calculation method considering thermal diffusivity resistivity improves the calculation accuracy and would be physically significant.

Multiscale Concurrent Atomistic-Continuum (CAC) modeling of multicomponent alloys

Strengthening in complex multicomponent systems such as solid solution alloys is controlled primarily by the dynamic interactions between dislocation lines and heterogeneously distributed solute species. Modeling of extended defect length scales in such multicomponent systems becomes prohibitively expensive, motivating the development of reduced order approaches. This work explores the application of the Concurrent Atomistic-Continuum (CAC) method to model dislocation mobility in random alloys at extended length scales. By employing recently developed average-atom interatomic potentials, the average “bulk” material response in coarse-grained regions interacts with true random solute species in the atomistic-scale domain. We demonstrate that spurious stresses in domain resolution transition regions are eliminated entirely due to the CAC formulation. Simultaneously, the key details of local stress fluctuation due to randomness in the dislocation core region are captured, and fluctuating stress smoothly decays to the long-range dislocation stress field response. Dislocation mobility calculations, for line lengths over 400 nm, are computed as a function of alloy composition in the model FeNiCr system and compared to full molecular dynamics (MD). The results capture the composition-dependent trends, while reducing degrees of freedom by nearly 40%. This approach can be readily extended to any system described by an EAM potential and facilitates the study of large-scale defect dynamics in complex solute environments to support computational alloy design.

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. In the current work, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

Incorporating elasticity into CALPHAD-informed density-based grain boundary phase diagrams reveals segregation transition in Al-Cu and Al-Cu-Mg alloys

The phase-like behavior of grain boundaries (GBs), recently evidenced in several materials, is opening up new possibilities in the design of alloy microstructures. In this context, GB phase diagrams are contributing to a predictive description of GB segregation and (interfacial) phase changes. The influence of chemo-mechanical solute-GB interactions on the GB phase diagram remains elusive so far. This is particularly important for multi-component alloys where the elastic interactions among solute atoms, of various sizes and bonding energies, can prevail, governing a complex co-segregation phenomenon. Recently, we developed a density-based model for GB thermodynamics that intrinsically accounts for GB elasticity in pure elements. In this work, we incorporate the homogeneous and heterogeneous elastic energies associated with the solutes into the density-based framework. We derive the multi-component homogeneous elastic energy by generalizing the continuum misfitting sphere model and extend it for GBs. The density-based free energy functional directly uses bulk CALPHAD thermodynamic data. The model is applied to binary and ternary Al alloys. We reveal that the elastic energy can profoundly affect the GB solubility and segregation behavior, leading to Cu segregation in otherwise Cu-depleted Al GBs. Consequently, GB segregation transition, i.e., a jump in the GB segregation as a function of alloy composition, is revealed in Al-Cu and Al-Cu-Mg alloy systems with implications for subsequent GB precipitation in these alloys. CALPHAD-informed elasticity-incorporated GB phase diagrams enable addressing a broader range of GB phenomena in engineering multi-component alloys.

Precipitation in reactor pressure vessel steels under ion and neutron irradiation: On the role of segregated network dislocations

The ultrahigh density of Mn-Ni-Si-Cu precipitates that form in irradiated reactor pressure vessels (RPV) result in hardening and embrittlement, which may limit the service life of aging nuclear reactors. Here, we quantitatively analyze solute segregation to, and precipitation on, network dislocations in irradiated low alloy RPV steels. The analysis is based on a broad thermodynamic framework, which allows proper identification of possible non-equilibrium perturbative effects of irradiation, like radiation induced segregation (RIS). For the first time, we quantify the segregation of Cu, Mn, Ni and Si to ≈ 5–10 nm network dislocation segments, typically separated by a string-of-pearl type array of MnNiSi precipitates (MNSPs); the MNSPs are appended to Cu rich co-precipitates (CRPs) in steels bearing this element. Detailed atom probe tomography (APT) data are reported for 16 RPV steels, with a wide matrix of tailored compositions, irradiated by both neutrons and 6.4 MeV Fe3+ ions at 320 and 290 °C, respectively. A key aspect of this study is that the very high displacement per atom (dpa) doses and radiation enhanced diffusion (RED) result in nearly full phase separation, allowing isolation of thermodynamic (equilibrium or non-equilibrium) effects. We characterize segregation and precipitates with a comprehensive set of descriptors under both ion and neutron irradiation, including: a) solute enrichment factors (EFs) at dislocations, as a function of alloy composition; and, b) matrix versus dislocation precipitates and their respective characteristics. Formation of these dislocation features can be due to RIS, or thermodynamic in origin, or both. Coupled with simple models, we show that the nucleation MNSP features in low Cu steels is enhanced by segregation. However, in typical supersaturated RPV steels, rapid growth of the precipitates is thermodynamically driven to a quantitatively predictable, nearly full phase separation mole fraction.

Application of two-step diffusion couple technique in high-throughput screening of optimal composition and aging temperatures for alloys design: A demonstration in binary Ni-Al system

In this paper, four binary Ni-13.4 at.% Al/Ni-17.7 at.% Al diffusion couples were first prepared and subjected to homogenization at 1573 K for 10,800 s, from which a continuous concentration profile formed. The three diffusion couples were then cooled down for aging at respective temperatures, i.e., 1173, 1123, and 1073 K, for 14400 s. The effect of composition and aging temperature on the aging microstructure was studied in detail by means of different experimental techniques and statistical analysis. The volume fraction, grain size, and shape factor of ?? precipitates in the three diffusion couples were plotted as a function of alloy composition and annealing temperatures. Together with the previously proposed evaluation function in which the phase fraction, grain size, and shape factor of ?? precipitates were chosen as the evaluation indicators, the optimal alloy composition and aging temperature for binary Ni-Al alloys with the best mechanical properties were evaluated, and finally validated by the measured hardness values. The successful demonstration of alloy design in the present binary Ni-Al alloys indicated that the two-step diffusion couple, together with the evaluation function for mechanic properties, should be of generality for high-throughput screening of optimal alloy composition and heat treatment process in different alloys.

Discovery of New Ti-Based Alloys Aimed at Avoiding/Minimizing Formation of α” and ω-Phase Using CALPHAD and Artificial Intelligence

In this work, we studied a Ti-Nb-Zr-Sn system for exploring novel composition and temperatures that will be helpful in maximizing the stability of β phase while minimizing the formation of α” and ω-phase. The Ti-Nb-Zr-Sn system is free of toxic elements. This system was studied under the framework of CALculation of PHAse Diagram (CALPHAD) approach for determining the stability of various phases. These data were analyzed through artificial intelligence (AI) algorithms. Deep learning artificial neural network (DLANN) models were developed for various phases as a function of alloy composition and temperature. Software was written in Python programming language and DLANN models were developed utilizing TensorFlow/Keras libraries. DLANN models were used to predict various phases for new compositions and temperatures and provided a more complete dataset. This dataset was further analyzed through the concept of self-organizing maps (SOM) for determining correlations between phase stability of various phases, chemical composition, and temperature. Through this study, we determined candidate alloy compositions and temperatures that will be helpful in avoiding/minimizing formation of α” and ω-phase in a Ti-Zr-Nb-Sn system. This approach can be utilized in other systems such as ω-free shape memory alloys. DLANN models can even be used on a common Android mobile phone.

Characteristics of High-Al-Composed Quantum Structure Under Strain Effects

A heterojunction field effect transistor has been studied by a model run self-consistently from the solution of the Schrodinger equation coupled with Poisson equation. The properties of the device drain current, the band structure of device, and the charge distribution have been obtained because of material composition. The efforts have shown that unique reason of having the high carrier concentration in heterostructures is to manage with the piezoelectric and spontaneous polarization. Simulation by means of polarization-related quantities in nitride-based heterostructure systems reveals that the device characterizations of nitride alloys are a linear function of alloy composition. Our simulation results are comparable to other theoretical calculations.

Exploring additive manufacturing as a high-throughput screening tool for multiphase high entropy alloys

High entropy alloys (HEA) exhibit exceptional and sometimes record-setting physical, thermal and mechanical properties. However, the vast composition space presents a significant practical challenge for optimization, particularly when relying on sequential use of conventional metallurgical fabrication and characterization methods. An efficient method for rapidly evaluating the properties of complex concentrated alloys is presented. Powder based directed energy deposition additive manufacturing was used to synthesize a broad range of compositions in a single metallurgical sample via in situ alloying. An investigation of the phase-property space was done by compositionally grading a transition metal-based HEA (CoCrFeMnNi) with several refractory metals (i.e., Ta, Nb, and Ti-6Al-4V). A high throughput microstructural-mechanical analysis method was also utilized to rapidly assess microstructure and hardness as a function of alloy composition. Compositions promoting solid solutions, multiple phases, and intermetallics were found to have a wide range of hardness and fabrication quality. These results are discussed in the context of alloy-specific microstructural characteristics and configurational entropy, along with relevant processing challenges.

Minority carrier lifetime and photoluminescence of mid-wave infrared InAsSbBi

Time-resolved photoluminescence measurements are reported for InAsSbBi alloys grown by molecular beam epitaxy with Bi mole fractions ranging from 0 to 0.8%, yielding minority carrier lifetimes on the order of hundreds of nanoseconds. The minority carrier lifetimes extracted from the time-resolved photoluminescence measurements are comparable to those of lattice-matched InAsSb grown at the same respective temperatures. Nomarski imaging shows that smooth, droplet-free surface morphologies are obtained in 1 μm thick InAsSbBi epilayers grown at temperatures between 360 and 380 °C. The alloy composition-dependent bandgap energies for the InAsSbBi samples are determined from temperature-dependent steady-state photoluminescence measurements and compared with the tetragonal distortion measured by x-ray diffraction to determine the Sb and Bi mole fractions of each sample. The minority carrier lifetime and the achievable extension of the InAsSb(Bi) cut-off wavelength are analyzed as functions of alloy composition and compared with the performance of InAsSb layers with similar growth parameters.